For certain applications, it is desirable to detect the presence of at least one object in a flow of images provided by a video sensor, for example, a camera. An example of application is video surveillance.
Detection methods are generally designed according to the nature of the object to be detected in the images. In particular, in the case of people detection, methods of face detection in images have been developed. An example of a face detection method implements Viola and Jones' algorithm. A face detection algorithm generally provides a score representative of the likeliness for a face to have been detected in the image.
A disadvantage of known object detection methods is that, in certain cases, the method cannot detect the presence of objects in the image even though an object is actually present. This corresponds to a detection failure.
Further, another disadvantage of known methods of object detection in images is that, in certain cases, these methods may indicate that an object has been detected in the image even though no object is present in the image. This corresponds to a wrong detection.
It is thus desirable to provide a method of object detection in an image which both has a decrease detection failure rate and a decreased wrong detection rate.